DocumentCode
1629195
Title
Financial trend forecasting with fuzzy chaotic oscillatory-based neural networks (CONN)
Author
Kwong, K.M. ; Wong, Max H Y ; Lee, Raymond S T ; Liu, James N K
Author_Institution
Dept. of Comput., Hong Kong Polytech. Univ., Hong Kong, China
fYear
2009
Firstpage
1947
Lastpage
1952
Abstract
This paper describes a methodology for financial prediction by using an advanced paradigm from computational intelligence - Chaotic Oscillatory-based Neural Networks (CONN) and aid with fuzzy membership function. The method uses financial market data to predict market trends over a certain period of time. This approach may have a wide variety of applications but from financial forecasting perspective, it can be used to identify and forecast market patterns for providing valuable and useful advices to investors for making investment decisions.
Keywords
financial data processing; fuzzy set theory; investment; neural nets; computational intelligence; financial market data; financial trend forecasting; fuzzy chaotic oscillatory-based neural networks; fuzzy membership function; investment decisions; Biological neural networks; Chaos; Cotton; Economic forecasting; Fuzzy neural networks; Neural networks; Neurons; Oscillators; Predictive models; Wind forecasting;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Systems, 2009. FUZZ-IEEE 2009. IEEE International Conference on
Conference_Location
Jeju Island
ISSN
1098-7584
Print_ISBN
978-1-4244-3596-8
Electronic_ISBN
1098-7584
Type
conf
DOI
10.1109/FUZZY.2009.5277326
Filename
5277326
Link To Document